Medical system, apparatus and method

ABSTRACT

According to some embodiments, there is provided a medical monitoring device that includes one or more sensors, wherein a sensor is adapted to sense a parameter of a patient and computator adapted to receive an output of at least one sensor and to compute a condition-index-value directly related to a condition of the patient.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.12/742,858, filed May 13, 2010, which is the U.S. National Stage ofInternational Application No. PCT/IL2007/001393, filed Nov. 13, 2007,the contents of each of which are expressly incorporated herein byreference in their entireties.

BACKGROUND

Medical monitoring devices are routinely used in various medicalsettings to provide crucial data regarding a patient's medicalcondition. The monitoring devices may be divided into two main groups:monitoring devices that are used to monitor parameters that are a directmeasure of one of the patient's physiological functions and monitordevice that are used to monitor parameters that are an indirect measureof the status of a physiological function. For example, a parameter thatis a direct measure for a physiological function is capnography that maybe used to measure and provides values of the CO₂ concentration in theventilated breath, which is a direct measure of the patients ventilationfunctioning. For example, a parameter that is an indirect measurement isblood pressure, which indirectly provides information regarding thefunctioning of the heart and the cardio vascular condition of thepatient.

Capnography is a non-invasive monitoring method used to continuouslymeasure CO₂ concentration in exhaled breath. The CO₂, which is aconstant metabolism product of the cells, is exhaled out of the body andthe concentration of the exhaled CO₂, also known as end tidal CO₂(EtCO₂) is an approximate estimation of the arterial levels of CO₂. Themeasurements of the CO₂ concentration in a breath cycle are performed bya capnograph and the results are a numerical value displayed also in agraphical format in the shape of a waveform named a capnogram. Thenumerical value of the results may be presented in units of pressure (mmHg) or percentile. The capnogram may depict CO₂ concentration againsttotal expired volume, but the more common capnogram illustrates CO₂concentration against time.

Analyzing the capnogram may yield valuable information about thepatient's clinical status. Normal capnogram exhibits one or more typicalwaveforms, each one represents a single respiratory cycle and deviationfrom the normal waveform may hint as to the clinical situation of thepatient. For example, an abnormally high basal line representsre-breathing of exhaled CO₂; a slow increase in CO₂ concentration mayhint to uneven emptying of the lungs; rising in CO₂ concentrationwithout reaching a plateau may hint to situations of asthma or otherlower airway obstruction, very small changes in CO₂ concentration mayindicate an apnea situation, and the like. In addition to displayingrespiratory cycles, a trend display is also available in which manyindividual consecutive breath cycles are compressed together so thatchanges over time may be easily distinguished, providing yet anadditional aid in assessing and monitoring the patient's ventilation andclinical profile.

Capnography is widely used today as an important tool for trackingpatient's ventilation status in various health care settings, such asEmergency Room (ER), Operation Room (OR), Intensive Care Unit (ICU) andEmergency Medical Services (EMS). Among the clinical applications inwhich capnography may be used are Cardiovascular (for example in CPR,shock, pulmonary embolism), Respiratory (for example, verification ofendotracheal tubing, mechanically ventilated patients, conditions suchas Asthma, hyperventilation, hypoventilation, apnea; Sedation (forexample during operation); Patient transport (both intra- andinter-hospital).

In addition to CO₂ concentration, various other parameters may beindicative (directly or indirectly) of the ventilation (respiratory)status of a patient. Such parameters may include, for example,saturation of oxygen in the blood cells and other organs, heart rate,respiration rate, breath flow rate, blood pressure, and the like.Combination of various parameters may yield an improved indicationclinical condition of the patient in general and of the ventilatorystatus of the patient in particular.

SUMMARY

The following embodiments and aspects thereof are described andillustrated in conjunction with systems, tools and methods which aremeant to be exemplary and illustrative, not limiting in scope. Invarious embodiments, one or more of the above-described problems havebeen reduced or eliminated, while other embodiments are directed toother advantages or improvements.

According to some embodiments there is provided a medical monitoringdevice that includes one or more sensors, wherein a sensor is adapted tosense at least one parameter of a patient and computator adapted toreceive an output of at least one sensor and to compute an index-valuedirectly related to a condition of the patient.

According to further embodiments, the parameter of a patient may includea respiratory related parameter, pulmonary related parameter, cardiacrelated parameter or any combination thereof. The parameter of a patientmay include respiration rate, EtCO₂, SpO₂, heart rate, or anycombination thereof. The one or more sensors may include a capnograph,pulse oximeter, heart rate monitor, or any combination thereof.

According to some embodiments, the index value may be in the range of 1to 10. An increase in the index value may be indicative of animprovement in a patient's condition. A decrease in the index value maybe indicative of a deterioration of a patient's condition.

According to some embodiments, the device computator may be adapted tocompute the index value according to an average of an output of at leastone sensor. The computator may further be adapted to compute theindex-value according to a medical significance of an output of at leastone sensor, wherein the medical significance may be determined bycorrelating the output value of the sensor and the ordinary level of amedical condition.

According to further embodiments, the device may be further adapted tocompute a trend of the index-value. The device may be further adapted tocompute a reliability index of the index-value. The device mayadditionally be adapted compute a pause frequency parameter.

According to further embodiments, the device may further be adapted toprovide medical recommendation. The medical recommendation may bedetermined according to the index value. The medical recommendation maybe determined according to the index value and a parameter related to aCO₂ waveform.

According to further embodiments, the device may further include a userinterface. The device may also include a graphic display of the indexvalue. The device may also provide indication correlating to a conditionof the patient. The condition may include hyperventilation,hypoventilation or both. The device may further display sub regions ofthe index value, wherein the sub regions correlate to a condition of thepatient.

According to some embodiments, there is provided a method for computingan index-value directly related to a condition of the patient, themethod includes: a medical monitoring device comprising one or moresensors, wherein a sensor is adapted to sense at least one parameter ofa patient and a computator adapted to receive an output of at least onesensor and compute said index value.

According to some embodiments, the at least one parameter of a patientmay include a respiratory related parameter, pulmonary relatedparameter, cardiac related parameter and or combination thereof. Theparameter of a patient may include respiration rate, EtCO2, SpO2, heartrate, or any combination thereof. The one or more sensors may include acapnograph, pulse oximeter, heart rate monitor, or any combinationthereof.

According to some embodiments, the index value may be in the range of 1to 10. An increase in the index value may be indicative of animprovement in a patient's condition. A decrease in the index value maybe indicative of a deterioration of a patient's condition.

According to some embodiments, the device computator may adapted tocompute the index value according to an average of an output of at leastone sensor. The computator may further be adapted to compute theindex-value according to a medical significance of an output of at leastone sensor, wherein the medical significance may be determined bycorrelating the output value of the sensor and the ordinary level of amedical condition.

According to further embodiments, the device of the method may befurther adapted to compute a trend of the index-value. The device may befurther adapted to compute a reliability index of the index-value. Thedevice may additionally be adapted compute a pause frequency parameter.

According to further embodiments, the device of the method may furtherbe adapted to provide medical recommendation. The medical recommendationmay be determined according to the index value. The medicalrecommendation may be determined according to the index value and aparameter related to a CO₂ waveform.

According to further embodiments, the device of the method may furtherinclude a user interface. The device may also display of the indexvalue. The device may also provide indication correlating to a conditionof the patient. The condition may include hyperventilation,hypoventilation or both. The device may further display sub regions ofthe index value, wherein the sub regions correlate to a condition of thepatient.

According to some embodiments, there is provided a medical system thatincludes a monitoring device comprising one or more sensors, wherein asensor is adapted to sense at least one parameter of a patient,computator adapted to receive an output of at least one sensor and tocompute an index-value directly related to a condition of the patientand a sampling unit adapted to sample breath from a patient.

According to some embodiments, the sampling unit of the medical systemmay include an oral nasal cannula.

According to some embodiments, the parameter of a patient may include arespiratory related parameter, pulmonary related parameter, cardiacrelated parameter or any combination thereof. The parameter of a patientmay include respiration rate, EtCO2, SpO2, heart rate, or anycombination thereof. The one or more sensors may include a capnograph,pulse oximeter, heart rate monitor, or any combination thereof.

According to some embodiments, the index value may be in the range of 1to 10. An increase in the index value is indicative of an improvement ina patient's condition. A decrease in said index value is indicative of adeterioration of a patient's condition.

In addition to the exemplary aspects and embodiments described above,further aspects and embodiments will become apparent by reference to thefigures and by study of the following detailed descriptions.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1A—A graph depicting the CO₂ medical significance level;

FIG. 1B—A graph depicting the respiration rate medical significancelevel;

FIG. 1C—A graph depicting the SpO₂ medical significance level;

FIG. 1D—A graph depicting the heart rate medical significance level; and

FIG. 2—A block diagram of a medical monitoring device, according to someembodiments.

DETAILED DESCRIPTION

In the following description, various aspects of the invention will bedescribed. For the purpose of explanation, specific configurations anddetails are set forth in order to provide a thorough understanding ofthe invention. However, it will also be apparent to one skilled in theart that the invention may be practiced without specific details beingpresented herein. Furthermore, well-known features may be omitted orsimplified in order not to obscure the invention.

As referred to herein the terms “user”, “medical user” and “health careprovider”, “health care professional” may interchangeably be used. Theterms may include may health care provider that may treat and/or attendto a patient. A user may include, for example, a nurse, respiratorytherapist, physician, anesthesiologist, and the like.

As referred to herein, the terms “device”, “monitoring device” and“medical device” may interchangeably be used.

As referred to herein, the terms “patient”, subject” may interchangeablybe used and may relate to a subject being monitored by any monitoringdevice for any physical-condition related parameter and/or healthrelated parameter.

As referred to herein, the terms ordinary, normal, typical, standard,common may interchangeably be used.

As referred to herein, the terms “condition-index-value” and “indexvalue” may interchangeably be used.

Currently, in most health care settings, patient related parameters(data) are collected on line and may provide various health careproviders, such as a nurse, a physician, a respiratory therapist, ananesthesiologist and the like, with information regarding the patient'sstatus. The information routinely presented may include various types ofinformation regarding various parameters that may be sensed by varioussensors. Viewing and interpreting the information presented maysometimes be a cumbersome, complicated and time consuming task for thehealth care provider.

According to some embodiments, there is a need to analyze the variouspatient related parameters (data) that are collected on line, in realtime, and provide the health care providers with a more comprehensible,meaningful, intuitive, clearer and useful information about the patientstatus. The data collected may be calculated and the information to thehealth care provider may be provided in the form of acondition-index-value that is directly related to the clinical conditionof the patient. The condition-index-value may be calculated based uponvarious parameters of a patient that may be sensed/measured byappropriate sensors. Providing the condition-index value to the healthcare provider may result in a clear indication for the health careprovider to realize when more medical attention is required for a givenpatient and for a given patient condition. Since the condition-indexvalue and the indications resulting therefrom may be deduced fromseveral parameters, the sensitivity of monitoring the patient conditionmay be increased, and earlier warnings with earlier intervention may beanticipated.

According to further embodiments, the condition-index-value may becalculated/computed by a device, such as, for example, a monitoringdevice. The monitoring device may include one or more sensors that maybe used to sense and/or measure, and/or calculate various health relatedparameters. The monitoring device may include any known medicalmonitoring device, such as, for example, capnograph, oxymeter,spirometer, heart rate sensors, blood pressure sensors, ECG, EEG,Ultrasound, and the like, and any combination thereof. Based on thevarious measurements, the device may calculate thecondition-index-value, and display the index alone or in combinationwith the various patient parameters that may be sensed/measured byappropriate sensors. In addition, the device may also provide medicalrecommendations to the user based on the analysis of the collectedpatient data. Moreover, the device may track and notify the health careprovider regarding changes over time of the patient condition. Forexample, the device may notify the health care provider if the patientcondition is stable, improving or deteriorating.

According to some embodiments, the condition-index-value may be aunit-less value in any predetermined range, such as, for example, in therange of 1 to 100. For example, condition-index-value may in the rangeof 1 to 10, wherein 10 indicates the best condition, and 1 indicates theworst condition. Within the range of 1 to 10, sub ranges (subdivisions)may be assigned. For example, a sub-range from 8 to 10 indicative of astable, normal condition, where no intervention is needed. A sub-rangeof 6-7 may be indicative for the health care provider that moreattention is needed patient re-evaluation is recommended. A sub range ofbelow 5 may indicate to the health care provider that intervention isneeded and patient re-evaluation may be necessary. In addition, thevarious sub-ranges of the condition-index-value may be assigneddifferent graphical signs, when displayed to the health care provider.The different graphical signs may include, for example, differentcolors, different units, different letters, and the like. For example,for condition-index-value in the sub-range of 8 to 10, the value may becolored green, for condition-index-value in the sub-range of 5 to 7 thevalue may be colored yellow and for condition-index-value in thesub-range of below 5, value may be colored red. In addition, variousother visual indicators may also be used to indicate changes that may becorrelated with known physical conditions, such as for example, up anddown arrows that may indicate, for example an increase or decrease,respectively, in one or more measured parameters.

According to some embodiments, the condition index value may becalculated by various means, such as, for example by use of mathematicalequations, algorithms, formulas, and the like that may take intoconsideration one or more of the values or derivatives of the values ofthe parameters that are being measured by the monitoring device.

According to further embodiments, the change of thecondition-index-value over time (referred to herein ascondition-index-value trend) may be displayed graphically. The graphicdisplay may exhibit the condition-index-value trended over the last “n”(time units) of monitoring. For example, n may be any time period in therange of 5 minutes to 12 hours. This display may be used to indicate thepatient's status, such as, for example: stable, improving,deteriorating, as well as providing a depiction of the rate and changeof the patient's status. Displaying of the condition-index-value trendmay simplify the assessment of the changes in the condition of thepatient as compared to assessing the patient condition based on thetrend of the individual parameters When looking at the trends of theindividual parameters, it may not be easy and intuitive to determine thepatients status and change in status, without taking into considerationthe absolute values of the individual parameters and their interactions.

According to further embodiments, the condition-index-value trend may bedepicted as a graphic display of the condition-index-value over time.The duration period of the trend may be chosen to be over any timeperiod in the range of, for example between 5 minutes to 12 hours of thelast measurements. The resolution of the graphical display may changeaccordingly in correlation to the selected time period.

According to further embodiments, an index of reliability (referred toherein also as “reliability index” “RI”) may also be determined. Theindex of reliability (referred to herein also as “reliability index” or“RI”) may provide a measure of the reliability of the data and morespecifically, the reliability of the condition-index-value. For example,the reliability index may be used to predict and anticipate artifacts.The reliability index may be determined, for example, by analysis of theCO₂ waveforms, as depicted by a capnogram. If breath flow is alsomeasured, its waveforms may also be used for this purpose. The use ofbreath flow measurements may refine and improve the index ofreliability. Breath flow waveforms strongly complement the waveformscreated by the CO₂ measurement, since both measurements representessentially the same event, which is the breath cycle. While the breathflow relates to the envelope of the waveform, the CO₂ relates to the CO₂concentration within the envelope. Using both parameters may betterreveal and uncover what is a measurement noise, artifact, and the like.

According to additional embodiments, a pause frequency parameter may bedetermined. This parameter may include a measure of events wherein nobreathing is detected, over a period of time. The events of lack ofbreathing may include, for example pause and apnea events, and the pausefrequency parameter may include a measure of patient's pause and apneaevents over a period of time. The pause frequency parameter may becalculated from the CO₂ waveform, as obtained by the capnogram. A pauseevent may be defined, for example, as any inhalation stage that persistsfor longer than any number of seconds in the range of, for example, 5 to40 seconds (such as for example 20 seconds), and proceeds after anexhalation period lasting less than any number of seconds in the rangeof, for example, 5 to 20 seconds (such as, for example, 10 seconds). Thetime periods may be determined, for example, according to the averagetime of the last three exhalation cycles. Such determination of a pauseevent may be used to exclude a slow, rhythmic breathing pattern frombeing defined as a group of pause events. In addition, a maximum timeout of, for example, 100 seconds may be determined. If a pause isdetected, a new pause can only be counted if at least three new, validbreath cycles were detected beforehand. Thus, the Pause FrequencyParameter may be defined by the number of pause events per period oftime (such as for example, an hour). The pause frequency may be updatedat any time intervals, such as for example, every 5 minutes, after theperiod of 1 hour. The values of the pause frequency may further bestored and used for the display of the pause frequency trend, whereinthe trend data represent the change of the pause frequency over time.According to some exemplary embodiments, during the first hour (wheninsufficient data has accumulated), a value may be provided and updated,for example, every 15 minutes until 1 hour has been reached (whereinduring this time period the frequency is calculated as if it wascalculated for 1 hour). During this time period an indication showingthat the pause frequency is still based on a shorter period than 1 hourmay be displayed. Since the health care provider, such as a nurse, maynot be constantly present next to the patient and/or the monitoringdevice, and may not constantly track (monitor) the patient condition, aparameter, such as the pause frequency parameter, which is a periodictype effect may not easily be observed by the health care provider ifnot otherwise tracked by the monitoring device. In addition, accordingto further embodiments, the pause amplitude parameter may also bedetermined. The pause amplitude parameter may be determined bymeasurements of the time length (such as, for example, in the range of 5to 60 seconds) of each of the detected pause events and the dispersionof the time lengths of the pause events over a period of time (such as,for example, over a time period of 60 minutes).

According to some embodiments, the device may further include anddisplay medical recommendations to the health care professionals. Themedical recommendations may be deduced from analysis of at least some ofthe individual parameter values and patterns and comparison of themeasured values and patterns to the known ranges and patterns of theindividual parameters. These recommendations may be displayed inaddition to the indications derived from the calculatedcondition-index-value.

According to some embodiments the medical device may include a userinterface that may allow the user to select the data to be displayed andto control various operating parameters. Moreover, different displaysmay be included to accommodate different needs of the different users(such as a nurse, a physician, an anesthesiologist, and the like).Allowing the user to change the view of the data may permit the user totoggle through the different levels of information for furtherevaluation of a condition. For example, the basic screen may be displaythe condition-index-value and the condition-index-value trend data.Changing to the next display may reveal the actual (measured) datavalues and the trends of the values that relate to the parameters fromwhich the condition-index-value is calculated. Further toggling thedisplay may provide the pause frequency and other related analysis andcalculation. The use of the various displays may also allow the user tofocus on the parameters that caused an indication of an event and/orrecommendation to the user.

According to further embodiments, the user interface may also allow theuser to enter information that is characteristic for each patient. Theuse of characteristic patient information is necessary to allow accuracyof the various measurements and calculations. Such information mayinclude, for example age, weight, height, sex, and the like, of thespecific patient. In addition, classification detection means of variouspatients may be utilized, wherein the classification may be based onparameters such as, for example, age group, weight group, sex, and thelike. Using such classification may allow the monitoring device tocorrect its settings to be appropriate for that relevant patient typeand environment.

According to some exemplary embodiments, the condition-index-value mayrepresent the respiratory status and/or the pulmonary status and/or thecardiac status of the patient. This may be accomplished by providing anindex value that is calculated based upon various respiratory, pulmonaryand cardiac parameters, such as, for example, but not limited to: EtCO₂,respiratory rate, breath flow rate, spirometry readings, O₂ saturation,SpO₂, blood pressure, blood gases, heart rate, Electrocardiogram (ECG),Electroencephalogram (EEG), Ultrasound measurements, such as heartechogram, and the like and any combination thereof.

As referred to herein, the term EtCO2 relates to End tidal CO2. The CO₂is exhaled out of the body and the concentration of the exhaled CO₂,also known as end tidal CO₂ (EtCO₂) is an approximate estimation of thealveolar CO₂ pressure and thus of the arterial levels of CO₂. Themeasurements of the CO₂ concentration in a breath cycle are performed bya capnograph and the results are a numerical value displayed also in agraphical format in the shape of a waveform named a capnogram. Thevalues of EtCO2 may be measured in units of pressure, such as, forexample, mmHg.

As referred to herein, the term SpO2 relates to the saturation ofperipheral oxygen. It is a measurement of the amount of oxygen attachedto the hemoglobin in red blood cell in the circulatory system. SpO2values are generally given as a percentage (for example, normal value isabove 96%). SpO2 may be monitored and measured by various monitors, suchas for example, Pulse Oximeter.

As referred to herein, the term Respiration Rate (RR) is defined as thenumber of breaths taken in a minute and it may change under variousphysiological and medical conditions. The rate may be abnormally high(tachypnea), abnormally low (bradypnea) or non-existent (apnea).

As referred to herein, the term Heart Rate (HR) relates to the number ofheart pulses (beats) in a minute.

As referred to herein, the term “hypoventilation” relates to a state ofrespiratory depression that may occur when ventilation is inadequate toperform needed gas exchange. Hypoventilation may cause an increasedconcentration of carbon dioxide and respiratory acidosis.Hypoventilation may be caused by various medical conditions and/or byuse of some drugs and medicines.

As referred to herein, the term “hyperventilation” relates to a state ofbreathing faster and/or deeper than necessary, thereby reducing thecarbon dioxide concentration of the blood below normal.

According to some exemplary embodiments, the condition-index-value maybe a Pulmonary/Respiratory Index value (also referred to herein as “PI”)may be determined. The PI index may represent a measurement of thepatient's respiratory status. It may be deduced from various measuredparameters, such as, for example: EtCO₂, Respiration Rate, SpO₂ andHeart Rate. The PI may be indicative of the absolute patient condition.The PI may be a unit-less value in the range of 1 to 10, wherein 10indicates the best condition, and 1 indicate the worst condition. Withinthe range of 1 to 10, sub ranges (subdivisions) may be assigned. Forexample, a sub-range from 8 to 10 indicative of a stable, normalcondition, where no intervention is needed. A sub-range of 6-7 may beindicative for the health care provider that more attention is needed. Asub range of below 5 may indicate to the health care provider thatintervention and/or patient re-evaluation and/or change in therapy isrecommended. In addition, the various sub-ranges of thecondition-index-value may be assigned different graphical signs, whendisplayed to the health care provider. The different graphical signs mayinclude, for example, different colors, different units, differentletters, and the like. For example, for condition-index-value in thesub-range of 8 to 10, the value may be colored green, forcondition-index-value in the sub-range of 5 to 7 the value may becolored yellow and for condition-index-value in the sub-range of below5, value may be colored red. In addition, various other visualindicators may also be used to indicate changes that may be correlatedwith known medical conditions, such as for example, up and down arrowsthat may indicate, for example a state of hyperventilation andhypoventilation, respectively.

According to some embodiments, the PI index value may be determined byvarious ways, using various calculation methods and various algorithms,as further detailed below herein. Generally, the PI may be deduced fromvarious parameters and may be assigned the highest value, for example“10”, when the individual values of the various parameters are wellwithin their respective normal ranges. The PI value may decrease below“10” when the value of one or more of the individual parameters changesfrom the normal respective ranges for those parameters. The decrease ofthe PI value may be sharper when several individual parameters changetogether.

According to some embodiments, the PI value may be updated continuouslyand it may be calculated from an average of the values of the parametersthat are used to produce the PI value. In addition, the averaging timeused for the determination of the PI value may also be adaptive. Forexample, if there is an erratic measurement, the average time mayincrease. The erratic characteristics used for deciding the averagingtime may result, for example, from the respiratory rate values, the CO₂waveform, and any other suitable parameter that is used for thecalculation of the PI.

According to further embodiments, the PI value may also be indicative ofconditions such as hypoventilation and hyperventilation. When the PI isindicative of these conditions, an appropriate additional indicativesignaling may be displayed, such as, for example an upward arrow(indicative of hyperventilation) and downward arrow (indicative ofhypoventilation). The decision as to whether the patient's status is ineither hypoventilation or hyperventilation may be based for example,upon the Respiratory Rate, when respiratory rate is one of the measuredparameters.

According to some embodiments, there are various methods to calculatethe PI value. Generally, various parameters may be measured and used forthe calculation of the PI value. According to some exemplaryembodiments, the PI may be calculated based on measuring the values ofat least one of the parameters EtCO₂, Respiration Rate, SpO₂ and HeartRate. The real time values of these parameters may be measuredcontinuously. For example, an adaptive running average may be collectedfor all the 4 measured parameters (average EtCO₂, average respiratoryrate, average heart rate and average SpO₂). This adaptive runningaverage may be calculated by collecting the data displayed by themonitors that measure the parameters, each second, and averaging over aperiod of time (as explained below). In this way, the calculated averagetake into consideration not only the values collected over the last “x”number of seconds, but also the length of time the value was displayed.The PI may then be calculated using these average values. The averagingtime period may be calculated and defined using an adaptive typealgorithm. For example, the default time period may be in the range of 5to 60 seconds, such as for example, 30 seconds. The time may increase insteps of, for example, 2 to 30 seconds, such as, for example, in stepsof 15 seconds; and the maximum period of time may be in the range of 5to 180 seconds, such as, for example, 90 seconds, 120 seconds, and thelike. In order to evaluate if the data is stable or erratic, informationthat may be used to determine if averaging time is to be increased ordecreased, respectively, the parameter value of respiratory rate may beused. The standard deviation of the respiratory rate over the lastpredetermined period of time (such as, for example, 30 seconds) may becontinuously measured. If the standard deviation of the respiratory ratevalue is below a predefined threshold, then the averaging period doesnot change. If the standard deviation of the respiratory rate over thelast predetermined period of time is above the predetermined threshold,then the averaging period may be increased (for example, by 15 seconds).

According to some embodiments, the PI may be calculated by usingmathematic calculations. The calculation may be based on the measuringthe values of at least one of the parameters EtCO₂, Respiration Rate(RR), SpO₂ and Heart Rate (HR) and the calculated average of thoseparameters, as detailed above herein. The calculations may relay onknown defined ranges values for each of the measured parameters (incorrelation with the patient characteristics, as detailed below).Meeting predefined conditions of the various measured parameters valuesresult in an appropriate calculated PI value. For example, and asfurther detailed in Example 1, when the following conditions arerealized the PI be 10 or 9 and no arrows, indicative of changes incondition are displayed: If RR is >12 & <28 and EtCO₂ is ≧28 & <44 andSpO₂ is >94%, Then: PI=10. If RR is >12 & <28 and EtCO₂ is ≧28 & <44 andSpO₂>90% & <94%, Then: PI=9.

According to some embodiments, the PI may be calculated by usingmathematic calculations. The calculations may be based on multiplicationof the medical significance level (risk/probability level) that isassociated with each of the measured parameters. The medicalsignificance level of each of the measured parameters may be determinedby creating a graph, indexing tables, and the like, which correlate thevalue of the parameter with an ordinary (standard/typical,common/normal) level of a physical condition, such as, for exampleventilatory condition (such as breathing, respiration, exhaling,inhaling). The ordinary level of the physical condition may be in therange of 0 to 1, wherein 1 signifies the best physical condition and 0signifies the worse physical condition. Thus, for example, mathematicalfunctions may be provided for each of the measured parameters, where themaximum value of 1 may relate to a physical condition that is normal,and a minimum value of 0, may relate to a physical condition that isworst, such as for example, when no ventilatory performance is detectedat all. FIG. 1A illustrates a graph which depicts the medicalsignificance (risk levels) of the EtCO₂ parameter. As shown in FIG. 1A,the Y-axis is the ordinary level, in the scale of 0 to 1. The X-axis isthe level of EtCO₂ in units of mmHg. The medical significance curvedepicts the correlation curve between the ordinary level and the levelof EtCO₂ and the calculated curve that best correlates to the medicalsignificance curve. As can be deduced from the graph, at low EtCO₂ theordinary level value decreases to zero, indicative of moving towardsapnea, at high EtCO₂, although indicative of a dangerous condition (thatmay cause the blood to change its alkali level which may consequentlymany essential chemical processes), the ordinary level value does notfall to zero. The equation of the exemplary medical significance curve,which is illustrated in FIG. 1A may be described by the equation:Y₁=8E−06×3−0.0015×2+0.0724X−0.0496. FIG. 1B illustrates an exemplarygraph which depicts the medical significance levels of the respirationrate parameter. As shown in FIG. 1B, the Y-axis is the ordinary level,in a scale of 0 to 1. The X-axis is the respiratory rate in units ofnumber of breaths in a minute. The medical significance curve depictsthe correlation curve between the ordinary level and respiratory rateand the calculated curve that best correlates to the medicalsignificance curve. The equation of the exemplary medical significancecurve which is illustrated in FIG. 1B may be described by the equation:Y₂=4E−05×3−0.0043×2+0.1231X−0.0378. FIG. 1C illustrates an exemplarygraph which depicts the medical significance levels of the SpO₂parameter. As shown in FIG. 1C, the Y-axis is the ordinary level, in ascale of 0 to 1. The X-axis is the SpO₂ percentile. The medicalsignificance curve depicts the correlation curve between the ordinarylevel and the SpO₂ and the calculated curve that best correlates to themedical significance curve. The exemplary equation of the medicalsignificance curve which is illustrated in FIG. 1C may be described bythe equation: Y₃=−2E−05×3+0.004×2−0.2778X+6.1214. FIG. 1D illustrates anexemplary graph which depicts the medical significance levels of theheart rate parameter. As shown in FIG. 1D, the Y-axis is the ordinarylevel, in a scale of 0 to 1. The X-axis is the heart rate that ismeasured in number of beats in a minute. The medical significance curvedepicts the correlation curve between the ordinary level and the heartrate and the calculated curve that best correlates to the medicalsignificance curve. The equation of the exemplary medical significancecurve which is illustrated in FIG. 1D may be described by the equation:Y₄=8E−07×3−0.0003×2+0.0406X−0.4389. Similarly to creating andcalculating the correlation equations, indexing tables may also be usedto correlate between the ordinary level and the value of each of themeasured parameters.

According to some embodiments, the PI may be calculated by multiplyingthe medical significance factors of each of the measured parameters,obtained by the equations detailed above herein, and multiplying theresult by 10, to get an IP value in the range of 1 to 10. The equationmay be described as: PI=Y₁*Y₂*Y₃*Y₄. According to some exemplaryembodiments, the HR medical significance value (Y₄) is introduced to thecalculations, only if the medical significance value of one of the otherparameters is less than 0.8. In addition, the equations presented aboveherein are valid up to the following maximal values of the individualparameters: the EtCO₂ value reaches a value of about 90 mmHg, therespiratory rate reaches a value of about 50 bpm and SpO₂ reaches 50%.Above or below these values a default value of 0.2 may be used.

According to additional embodiments, if the calculated index is below 8,an upward arrow indication may be included if the respiration rate isgreater than a predetermined number of beats per minute (BPM), such as,for example, 24 BPM. A downward arrow indication may be included if therespiration rate is below a predetermined number of BPM, such as, forexample, 12 BPM. If the respiration rate is within a predeterminedrange, such as, for example between 12 and 24 BPM, no arrow indicationis provided.

According to further embodiments, the change of the PI value over time(PI trend) may be displayed graphically. The graphic display may exhibitthe PI trended over the last “n” (time units) of monitoring. Forexample, n may be any time period in the range of 5 minutes to 12 hours.This display may be used to indicate the patient's status, such as, forexample: stable, improving, deteriorating, as well as providing adepiction of the rate and change of the patient's status. Displaying ofthe PI trend may simplify the assessment of the changes in theventilatory condition of the patient as compared to assessing thepatient condition based on the trend of the individual parameters Whenlooking at the trends of the individual parameters, it may not be easyand intuitive to determine the patients status and change in status,without taking into consideration the absolute values of the individualparameters and their interactions, since both an increase or decrease inany of those parameters may be “good” (improvement) or “bad”(deterioration), depending on the absolute value of the parameter. Forexample, a decrease from a higher than normal absolute value towards thenormal absolute value may be considered “good”, while a decrease from anormal value to a lower than normal value may be considered “bad”.Likewise, an increase from a lower than normal value towards the normalvalue may be considered “goof”, while an increase from a normal value toa higher than normal value may be considered “bad”. The PI trend may bedepicted as a graphic display of the PI values over time. The durationperiod of the trend may be chosen to be over any time period in therange of, for example between 5 minutes to 12 hours of the lastmeasurements. The resolution of the graphical display may changeaccordingly in correlation to the selected time period. By providing atrend of the PI index an estimation of how the patients respiratorystatus is changing over time, such as, stable, improving ordeteriorating may be obtained. This may be attributed to the fact thatthe PI itself is an overall picture of the patients respiratory statusand the changes in value of this index may provide a clear picture towhether the patient condition is changing or not.

According to further embodiments, an index of reliability may also bedetermined. The index of reliability (referred to herein also as“reliability index” or “RI”) may provide a measure of the reliability ofthe data and more specifically, the reliability of the PI. For example,the reliability index may be used to predict and anticipate artifacts.The reliability index may be determined, for example, by analysis of theCO₂ waveforms, as depicted by a capnogram. If breath flow is alsomeasured, its waveforms may also be used for this purpose. The use ofbreath flow measurements may refine and improve the index ofreliability. Breath flow waveforms strongly complement the waveformscreated by the CO₂ measurement, since both measurements representessentially the same event which is the breath cycle. While the breathflow relates to the envelope of the waveform, the CO₂ relates to the CO₂concentration within the envelope. Using both parameters may reveal anduncover and assist in distinguishing between a valid measurement, anoise, an artifact, and the like. The reliability index may assist theuser (the health care provider) to decide if a low PI value or any ofthe other measured values is real (and represent a genuine clinicalevent), transient or an artifact. The reliability index may furtherassist the health care provider in assessing how much credibility may beattribute to the displayed PI value. In addition, the reliability indexmay allow the health care provider to detect artifacts, such as when themonitoring device is not placed properly on the patient, the monitoringdevice is not measuring properly, and the like. The reliability indexmay be determined from both analysis of the CO₂ waveform and respirationrate pattern. By obtaining data from controlled studies, thecharacteristic patterns attributed to artifacts may be defined. Analysisof the real time waveform depicted by the monitoring device andcomparison to the known artifact patterns may be used to calculate thereliability index.

According to additional embodiments, a pause frequency parameter may bedetermined. This parameter may include a measure of events wherein nobreathing is detected, over a period of time. The events of lack ofbreathing may include, for example pause and apnea events, and the pausefrequency parameter may include a measurement of the patient's pause andapnea events over a period of time. Very often patients may stopbreathing for short periods of time either because of mechanicalobstructions or sometimes because a central (brain) block. The pauses(apnea events) are periodic and their frequency may be indicative of thecondition of the patient. The pause frequency parameter may becalculated from the CO₂ waveform, as obtained by the capnogram. A pauseevent may be defined, for example, as any inhalation stage that persistsfor longer than any number of seconds in the range of, for example, 5 to40 seconds (such as for example 20 seconds), and proceeds after anexhalation period lasting less than any number of seconds in the rangeof, for example, 5 to 20 seconds (such as, for example, 10 seconds). Thetime periods may be determined, for example, according to the averagetime of the last three exhalation cycles. Such determination of a pauseevent may be used to exclude a slow, rhythmic breathing pattern frombeing defined as a group of pause events. In addition, a maximum timeout of, for example, 100 seconds may be determined. If a pause isdetected, a new pause can only be counted if at least three new, validbreath cycles were detected beforehand. Thus, the pause frequencyparameter may be defined by the number of pause events per period oftime (such as for example, an hour). The pause frequency may be updatedat any time intervals, such as for example, every 5 minutes, after theperiod of 1 hour. The values of the pause frequency may further bestored and used for the display of the pause frequency trend, whereinthe trend data represent the change of the pause frequency over time.According to some exemplary embodiments, during the first hour (wheninsufficient data has accumulated), a value may be provided and updated,for example, every 15 minutes until 1 hour has been reached (whereinduring this time period the frequency is calculated as if it wascalculated for 1 hour). During this time period an indication showingthat the pause frequency is still based on a shorter period than 1 hourmay be displayed. Since the health care provider, such as a nurse, maynot be constantly present next to the patient and/or the monitoringdevice, and may not constantly track (monitor) the patient condition, aparameter, such as the pause frequency parameter, which is a periodictype effect may not easily be observed by the health care provider ifnot otherwise tracked by the monitoring device. In addition, accordingto further embodiments, the pause amplitude parameter may also bedetermined. The pause amplitude parameter may include the time length(such as, for example, in the range of 5 to 60 seconds) of each of thedetected pause events and the dispersion of the time length of thosepause events over a period of time (such as, for example, over a timeperiod of 60 minutes).

According to some embodiments, the monitoring device may further includeand display medical recommendations to the health care professionals.The medical recommendations may be deduced from analysis of at leastsome of the individual parameters values and patterns and comparison ofthe measured values and patterns to the known ranges and patterns of theindividual parameters. These recommendations may be displayed inaddition to the indications derived from the calculatedcondition-index-value. The medical recommendations may be based on, forexample, the characteristics of the CO₂ waveforms (presented as acapnogram) and RI values. The recommendation provided to the health careprovider may include, for example such recommendation as: If CO₂waveforms are observed with characteristics indicative of a partialobstruction (such as long downward slope of the waveform), then thedevice may recommend “open airway” or “check airway”. If the CO₂waveforms are very low but exhibit an excellent form indicative of lowblood flow to lungs, then the device monitor may recommend: “check bloodpressure” or similar. The detection of known CO₂ waveform patterns,which are indicative of known patient conditions that should and couldbe treated to improve the patient care, may be used in triggering andissuing the recommendations to the health care professional. Forexample, it is very common that a patient entering partial obstructionpromote a waveform pattern wherein the downward slope of the capnogramincreases in time, with a gradual fall. In such an instance, anotification to the health care provider, such as, “check patientairway” may be issued. For example, if the CO₂ waveforms pattern becomevery rounded and low, which is indicative of a mechanical problem withthe cannula of the capnograph, a recommendation, such as, “check cannulainterface” may be issued. Those and other similar medicalrecommendations issued by the monitoring device may be presented inaddition to the indications derived from the PI. Examples of suchanalysis of waveform pattern may be found in publication: Krause B andHess D. R (2007) “Capnography for procedural sedation and analgesia inthe emergency department”, Ann Emerg Med. 50(2), Pages 172-81,incorporated herein by reference. For example, lower airway obstructionmay be seen by a capnogram showing a curved ascending phase andup-sloping alveolar plateau that indicate the presence of acutebronchospasm or obstructive lung disease; For example, distinguishingbetween bradypneic hypoventilation from hyperventilation may beperformed according to the CO2 wave form: while in the bradypneichypoventilation decreased respiratory rate, high amplitude and widecapnogram are detected, in hyperventilation an increase in respiratoryrate, low amplitude and narrow capnogram are detected.

According to some embodiments the medical device may further include auser interface that may allow the user to select the data to bedisplayed and to control various operating parameters. Moreover,different displays may be included to accommodate different needs of thedifferent users (such as a nurse, a physician, an anesthesiologist, andthe like). Allowing the user to change the view of the data may permitthe user to toggle through the different levels of information forfurther evaluation of a condition. For example, the basic screen may bedisplay the condition-index-value and the condition-index-value trenddata. Changing to the next display may reveal the actual (measured) datavalues and the trends of the values that relate to the parameters fromwhich the condition-index-value is calculated. Further toggling thedisplay may provide the pause frequency and other related analysis andcalculation. The use of the various displays may also allow the user tofocus on the parameters that caused an indication of an event and/orrecommendation to the user.

According to further embodiments, the user interface may also allow theuser to enter information that is characteristic for each patient. Theuse of characteristic patient information is necessary to allow accuracyof the various measurements and calculations. Such information mayinclude, for example, age, weight, height, sex, and the like of thespecific patient as well as other patient related information, such as,intubation (if the patient is intubated or not). For example, thepatient size and age may change the PI calculations: for an adult arespiration rate of 12 BPM would be normal, but 36 BPM would beconsidered high, whereas for a child, respiration rate of 12 may beconsidered low, while 36 BPM may be considered normal. In addition,classification detection means of various patients may be utilized,wherein the classification may be based on parameters such as, forexample, age group, weight group, sex, intubation, and the like. Usingsuch classification may allow the monitoring device to correct itssettings to be appropriate for that relevant patient type andenvironment. In addition, the user interface may allow automaticdetection of the type of the patient according to the measuringinterface being used. For example, a tubing interface used to measureCO₂ in breath may be different between an adult and a child andaccordingly, the user interface may automatically adjust the patientsettings to match the patient size group.

According to some embodiments there is thus provided a medical devicethat may be used to monitor patient's health condition, such asrespiratory and/or pulmonary and/or cardiac status. The device mayinclude, for example a canpongraphy device that may be adapted to senseand/or obtain measurements of various parameters other than CO₂. Suchparameters may include, for example, O₂ levels, O₂ partial pressure,such as SpO2, heart rate, blood pressure, and the like. The device mayfurther include a computator that may be used to receive informationfrom at least one of the sensors and to compute a condition-index-valuethat is directly related to a condition of the patient. The conditionindex value may be in the range of 1 to 10, wherein 10 indicates thebest condition while 1 indicates the worst condition. The monitoringdevice may further include one or display that may be used to presentthe data collected and calculated by the monitoring device. The displaymay present, for example, the calculated condition index in numericalformat and in indexed format, wherein different ranges along the 1-10scale of the calculated index may be assigned different colors; thechange (trend) of the calculated condition index value over time; thereliability of the calculated index value; values and patterns of thevarious parameters measured by the various sensors of the monitoringdevice; graphical indications regarding the status of the patient, suchas, for example, downward and upward arrows; and the like. Themonitoring device may further be adapted to issue medicalrecommendations based upon the calculated condition index value andother measured parameters. In addition, the monitoring device mayinclude a user interface that may allow the user to input patientrelated data that is specific for the patient, such as, for example,age, sex, size of the patient. The user interface may further allow theuser to choose the parameters to be displayed and the form in which theparameters may be displayed, such as for example in the form of graphs,numerical values, indicators, and the like.

Reference is now made to FIG. 2, which shows a block diagram of amedical monitoring device, according to some embodiments of theinvention. Medical monitoring device 200 includes two sensors:capnograph 202 and pulse oximeter 204. Medical monitoring device 200further includes computing unit 206 adapted to receive output parametersat least from capnograph 202 and from pulse oximeter 204. Computing unit206 is further adapted to compute a unit-less index-value directlyrelated to a respiratory status of the patient based on the outputparameters. Medical monitoring device 200 may further include moresensors, such as heart rate monitor 208, blood pressure monitor 210, ECG212 and EEG 214. Medical monitoring device 200 may further include userinterface 216 and display 218.

While a number of exemplary aspects and embodiments have been discussedabove, those of skill in the art will recognize certain modifications,permutations, additions and sub-combinations thereof. It is thereforeintended that the following appended claims and claims hereafterintroduced be interpreted to include all such modifications,permutations, additions and sub-combinations as are within their truespirit and scope.

EXAMPLES Example 1 Calculating PI Value Using Mathematical Methods

As detailed above herein, any of the parameter values used for thecalculation of the PI is based on the calculated value of the averageEtCO₂, average respiratory rate, average heart rate and average SpO₂.

EtCO₂—End tidal CO₂ is measured in units of mmHgRR—Respiration Rate is measured in number of breaths per minuteSpO₂—is measured in percentileHR—Heart Rate is measured in pulses per minute

PI≧9-10

When the following conditions are realized the index will be 10 or 9 andno arrows, indicative of hyper or hypoventilation, are displayed:

If RR is >12 & <28 And EtCO2 ≧28 & <44 And SpO2 >94% Then: Index = 10 IfRR is >12 & <28 And EtCO2 ≧28 & <44 And SpO2 >90% & <94% Then: Index = 9

PI≦7 and Indication of Hypoventilation

If RR is ≦5 Then: Index = 4 down If RR is ≦8 And EtCO2 ≧64 Or EtCO2 ≦12Or SpO2 ≦86% Then: Index = 3 down If RR is ≦5 And EtCO2 ≧64 Or EtCO2 ≦12And SpO2 ≦86% Then: Index = 1 down If RR is ≦5 And SpO2 ≦86% Then: Index= 2 down If RR is >5 & ≦8 And EtCO2 ≧46 & <64 Or EtCO2 ≦24 & >12 AndSpO2 ≦90% & >86% Then: Index = 5 down If RR is >5 & ≦8 And EtCO2 ≧46 &<64 Or EtCO2 ≦24 & >12 And SpO2 >90% Then: Index = 6 down If RR is >8 &≦12 And EtCO2 ≧55 Or EtCO2 <18 And SpO2 ≦90% Then: Index = 6 down If RRis >8 & ≦12 And EtCO2 ≧55 Or EtCO2 <18 And SpO2 >90% Then: Index = 7down.

PI≦8 and No Indication of Hyperventilation or Hypoventilation:

If RR is >12 & <16 And EtCO₂ ≧64 Or EtCO2 <12 And SpO2 <90% Then: Index= 6 If RR is >12 & <16 And EtCO₂ ≧64 Or EtCO₂ <12 And SpO₂ >90% Then:Index = 7 If RR is >12 & <16 And EtCO2 ≧44 & <64 Or EtCO2 ≦24 & >12 AndSpO2 <90% Then: Index = 7 If RR is >12 & <16 And EtCO2 ≧44 & <64 OrEtCO2 ≦24 & >12 And SpO2 >90% Then: Index = 8

PI≦8 and Indication of Hyperventilation

If RR is ≧40 And HR is ≧110 Then: Index = 4 Up If RR is ≧40 And EtCO2≧50 And HR is ≧110 Then: Index = 3 Up If RR is ≧40 And EtCO2 ≧50 And HRis ≧110 And SpO2 ≦90% Then: Index = 2 Up If RR is ≧40 And EtCO2 ≧44 &<50 And HR is ≧100 And SpO2 ≦90% Then: Index = 3 Up If RR is ≧40 AndEtCO2 ≧44 & <50 And HR is ≧100 And SpO2 >90% Then: Index = 4 Up If RR is≧32 & <40 And HR is ≧100 Then: Index = 8 Up If RR is ≧32 & <40 And HR is≧100 & <120 And EtCO2 ≧44 & <50 Then: Index = 7 Up If RR is ≧32 & <40And HR is ≧100 And EtCO2 ≧44 And SpO2 ≦90% Then: Index = 6 Up If RR is≧32 & <40 And HR is ≧120 And EtCO2 ≧55 Then: Index = 5 Up If RR is ≧28 &<32 And HR is ≧120 And EtCO2 ≧55 Then: Index = 6 Up If RR is ≧28 & <32And HR is ≧100 And EtCO2 ≧44 Then: Index = 7 Up And EtCO2 ≧44 & <64 OrEtCO2 ≦24 & >12 And SpO2 <90% Then: Index = 7 up If RR is >16 & <28 AndEtCO2 ≧44 & <64 Or EtCO2 ≦24 & >12 And SpO2 <90% Then: Index = 7 up

What we claim is:
 1. A method for computing a single unit lessindex-value indicative of a respiratory status a patient, the methodcomprising: continuously sensing at least two parameters of a patient,using two or more sensors, wherein said two or more sensors comprise atleast a capnograph and a pulse oximeter; and continuously computing asingle unit-less index-value based on an integration of at least twooutput parameters received at least from the capnograph and the pulseoximeter, wherein a change in the single unit-less index-value isindicative of a change in the respiratory status of the patient.
 2. Themethod of claim 1, wherein the at least two parameters of a patientcomprise a respiratory related parameter, pulmonary related parameter,cardiac related parameter and or any combination thereof.
 3. The methodof claim 1, wherein the at least two parameters of a patient compriserespiration rate, EtCO2, SpO₂, heart rate, or any combination thereof.4. The method of claim 1, wherein the two or more sensors furthercomprises a heart rate monitor, blood pressure monitor,Electrocardiography (ECG), Electroencephalography (EEG) or anycombination thereof.
 5. The method of claim 1, wherein the singleunit-less index-value is in the range of 1 to
 10. 6. The method of claim1, wherein the single unit-less index-value is in the range of 1 to 100.7. The method of claim 1, wherein an increase in the single unit-lessindex-value is indicative of an improvement in a patient's condition. 8.The method of claim 1, wherein a decrease in the single unit-lessindex-value is indicative of an improvement in a patient's condition. 9.The method of claim 1, wherein a decrease in the single unit-lessindex-value is indicative of a deterioration of a patient's condition.10. The method of claim 1, wherein an increase in the single unit-lessindex-value is indicative of a deterioration of a patient's condition.11. The method of claim 1, wherein the single unit-less index-value iscomputed according to an average of the at least two output parameters.12. The method of claim 1, wherein computing the single unit-lessindex-value is comprises mathematical operation of a medicalsignificance level of each of the at least two output parameters. 13.The method of claim 12, wherein the mathematical operation comprisesmultiplication.
 14. The method of claim 1, wherein the medicalsignificance level of each of the at least two output parameters isdetermined by correlating the output value of each of the at least twooutput parameters with that of a normal level.
 15. The method of claim1, further comprising computing a trend of said single unit-lessindex-value.
 16. The method of claim 1, further comprising computing areliability index of said single unit-less index-value.
 17. The methodof claim 1, further comprising providing a pause frequency parameter.18. The method of claim 1, further comprising providing a medicalrecommendation.
 19. The method of claim 18, wherein said medicalrecommendation is determined according to the single unit-lessindex-value.
 20. The method of claim 18, wherein said medicalrecommendation is determined according to the single unit-lessindex-value and a parameter related to a CO₂ waveform.
 21. The method ofclaim 1 further comprising a user interface.
 22. The method of claim 1further comprising graphically displaying the single unit-lessindex-value on a graphic display.
 23. The method of claim 1 furthercomprising graphically displaying a trend of the single unit-lessindex-value.
 24. The method of claim 1, further comprising providingindications correlating to a status of the patient.
 25. The method ofclaim 24, wherein the status comprises hyperventilation, hypoventilationor both.
 26. The method of claim 1, wherein the change in the singleunit-less index-value is displayed as up and down arrows indicatinghyperventilation and hypoventilation respectively.
 27. The method ofclaim 1, further comprising graphically displaying a sub-range to whichthe single unit-less index-value is assigned, wherein the sub-rangecorrelates to a level of normality of the respiratory status and/or towhether medical intervention is required.
 28. The method of claim 27,wherein the sub-range is displayed with a different graphical signaccording to the level of normality of the respiratory status and/or towhether medical intervention is required.
 29. The method of claim 1,further comprising correlating the at least two output parameters to aset of predefined conditions.
 30. A medical system comprising: amonitoring device comprising two or more sensors adapted to sense atleast two parameters of a patient, wherein said two or more sensorscomprise at least a capnograph and a pulse oximeter; a computatoradapted to continuously receive at least two output parameters at leastfrom said capnograph and said pulse oximeter and to compute a singleunit-less index-value based on integration of said at least two outputparameters; and a sampling unit adapted to sample breath from a patient.31. The medical system of claim 30, wherein said sampling unit comprisesan oral nasal cannula.
 32. The medical system of claim 30, wherein saidat least two parameters of a patient comprises a respiratory relatedparameter, pulmonary related parameter, cardiac related parameter or anycombination thereof.
 33. The medical system of claim 30, wherein said atleast two parameters of a patient comprises respiration rate, EtCO2,SpO₂, heart rate, or any combination thereof.
 34. The medical system ofclaim 30, wherein said two or more sensors comprise a heart ratemonitor, blood pressure monitor, Electrocardiography (ECG),Electroencephalography (EEG) or any combination thereof.